1. Field of the Invention
The present invention is related generally to an improved data processing system and in particular to a method and apparatus for processing data. More particularly, the present invention is directed to a computer implemented method, apparatus, and computer usable program code for automatically identifying a customer in a retail environment and dynamically generating customized marketing messages for the identified customer.
2. Description of the Related Art
In the past, merchants, such as store owners and operators, frequently had a personal relationship with their customers. The merchant often knew their customers' names, address, marital status, ages of their children, hobbies, place of employment, anniversaries, birthdays, likes, dislikes and personal preferences. The merchant was able to use this information to cater to customer needs and push sales of items the customer might be likely to purchase based on the customer's personal situation. However, with the continued growth of large cities, the corresponding disappearance of small, rural towns, and the increasing number of large, impersonal chain stores with multiple employees, the merchants and employees of retail businesses rarely recognize regular customers, and almost never know the customer's name or any other details regarding their customer's personal preferences that might assist the merchant or employee in marketing efforts directed toward a particular customer.
One solution to this problem is directed toward using profile data for a customer to generate personalized marketing messages that may be sent to the customer by email, print media, telephone, or over the World Wide Web via a web page for the merchant. Customer profile data typically includes information provided by the customer in response to a questionnaire or survey, such as name, address, telephone number, gender, and indicators of particular products the customer is interested in purchasing. Demographic data regarding a customers age, sex, income, career, interests, hobbies, and consumer preferences may also be included in customer profile data.
In an ideal situation, an advertising computer then generates a customer advertisement based on the customer's profile. For example, one version of an advertisement may be directed to selling fruit juice to children while another version of the advertisement may be directed to selling the same fruit juice to adults. However, this method only provides a small number of pre-generated advertisements that are directed towards a fairly large segment of the population rather than to one individual. In other words, the same advertisement for selling the fruit juice to an adult may be provided to a soccer mom and to a college student, despite the fact that the soccer mom and college student have very different tastes, attitudes, preferences, financial constraints, and/or goals.
In another solution, user profile data, demographic data, point of contact data, and transaction data are analyzed to generate advertising content for customers that target the information content presented to individual consumers or users to increase the likelihood that the customer will purchase the goods or services presented. However, current solutions do not utilize all of the potential dynamic customer data elements that may be available to a retail owner or operator for generating customized marketing messages targeted to individual customers. For example, a person might be recently unemployed or have had a recent lifestyle change due to divorce or perhaps a death in the family. Other data pieces are needed to provide effective dynamic one-to-one marketing of messages to the potential customer. Therefore, the data elements in prior art only provides approximately seventy-five percent (75%) of the needed data.